Final Delivery: SkullHunters

Final Video / Hired Commercial

The SkullHunters needed an app for collaborative recruting in the company. We believe we have achieved exactly that, as a custom app in the cloud.

Initial mockup

Frontpage_mock Candidate%20Dashboard_mock





The frontpage gives the recruiters updated statistics on the recruting process, grabbing graphs from Excel sheets and presenting data from the list of candidates. The recruiters and precruiters can like candidates, and when a candidate gets above a predefined number of likes, a workflow is initiated sending an e-mail to the recruiters for that position.

Fuck off!

fuckoff 3

The candidates can be vetoed – or “fucked off” – by recruiters. When this happens, a notification is sent to the recruiters of this position, and if they got a Pebble watch they can even receive notification directly on their watch. Read more about this here.

The candidate dashboard


The candidate dashboard shows different sources of information of the candidate. it goes about getting search results from bing, key info and shared contacts from linkedin as well as information on the current employer. Collaborating on the candidate happens using Yammer, and it’s therefore very easy for anyone to join the discussion.

The “previous colleagues” in the top corner shows information from an old SharePoint 2007 legacy system the SkullHunters aquired, retrieving data via the Azure Service Bus.

Force full crawl of your tenant in SharePoint Online

The SkullHunters IT-Pro’s (SkullPro) constantly need to be on top of the search schema, refining and updating as the different recruiting apps materializes. Often changes needs to be done to the schema, changing Refinable, Sortable and other settings of managed properties.

Unfortunately in the SharePoint Online admin interface you cannot force a full crawl via the admin user interface. What does the SkullPro do? He creates his own script for forcing a full crawl of the tenant.

The script establishes a link with the SPO site, then for each web it calls the processweb function which increments the vti_searchversion property of the web. This will trigger a fulll crawl of the web the next time the web is crawled by SPO.


The script is called from the SharePoint online management shell, pointing to the SPO tenant and passing a username and password.

.\reindex-spo.ps1 -url -username “” –password “pass@word1

With this post, the SkullHunters are hoping for the following badges:

Nasty Hacker

Power of the Shell

Note that the script was not written during the challenge, but it was in fact UTILIZED and is a useful tool!

Doing dirty work for the community

To have a chance to be at Voksenåsen at ASPC 2015, we need to make a good impression on the hotel staff! People have been throwing the cigarette butts all round outside, when there’s clearly a pile of cigarettes!

With this video we’re clearly showing that we’ll do anything for the community – even pick up peoples cigarette butts without gloves!


We’re hoping for the following badge

embedding yammer comments and likes

We have changed the yammer integration from using the oob yammer apps, to using the yammer embed api

This way we can have comments related to the different candidates and also have yammer likes on the different candidates

we use a content editor wp on the page and integrate against the API using the following code:

<script type=”text/javascript” src=””></script>
<div id=”embedded-like”></div>
<div id=”embedded-feed”></div>
<script type=”text/javascript”>
container: “#embedded-like”,
network: “”,
action: “like”
container: “#embedded-feed”,
feedType: “open-graph”,
config: {
header: false,
footer: false

This is what it looks like. Note that this is all on the same aspx, but with different parameters passed to the page. As such the yammer api treats them as two different pages, making likes and comments unique for that candidate

yam1 yam2

In this post we’re aiming for the “Yam Yam Gimme Some” Badge


Embedded F*ck off-notifications using JSON

The precruiters using the SkullHunters’ Hired-app want to keep up with changes to the candidate board, even when on the road or away from a pc. It’s especially important to know when a candidate is vetoed (or ‘fucked off’) by someone.


Using a notification web service, JSON and a Pebble Smartwatch, a notification gets sent straight to the precruiters’ wrists in a mere second whenever someone F*cks off a candidate.

When a user clicks “F*ck off” on a candidate, the candidate gets removed from the candidate’s list in an exploding fashion. A JSON POST gets sent to the web service, containing the message

“SkullHunters: {CurrentlyLoggedOnUser} just f*cked off {CandidateName}”.
The web service then forwards the notification to an iPhone App which subscribes to notifications from the service, which in turn forwards it to the Pebble Smartwatch.

In this post we’re aiming for the Embedding Numbnut-badge


Data Mining from MOSS 2007

The Appsters SkullHunters have leveraged their previous solution which pulls straight forward data from MOSS 2007 legacy system using the Azure Service Bus:

We’re now mining this data, mining former colleagues of candidates and displaying them in their respective dashboards.


With this solution, we’re aiming for


Yammer integrating our dashboards

Whether or not a candidate will be a valuable asset to our organization is an important conversation that should include as many of our colleagues as possible. Having a discussion board or even a sharepoint social feed on our Candidate dashboard is a good option, but it will limit the discussion to SharePoint.

To reach an even wider audience we’re therefor using Yammer for commenting on candidates.

Here is the commenting feed on our candidate dashboard


This is how the conversation looks in Yammer


With this submission we’re going for this badge


Using cross site publishing to sell off candidates

Top management at Appsters Skullhunters have decided its time to monetize candidates in Hired that has been in our system a while and have not generate much buzz. The idea is to offer these candidates for sale to selected partners on our extranet.

To accomplish this we first publish our candidates list as a catalog. Note that we use current employer as the navigation setting.catalog2

Next we set up a mapping for the likes column to a managed property to allow filtering on likes


We have crated a new site collection in our SharePoint tenant where we have set up a catalog connection to the candidates catalogcatalog4

We tune the Content Search webparts included to filter on candidates created more than 14 days ago and with few likes.


We also include a content search webpart on the front page which shows candidates sorted on time descending.

This is the front page. Please note that we are withholding most of the information for these candidates. Also note that candidates with few likes are featured as “on sale”, we really do not want to hold on to these.

Front page of the extranet site


Drilling down on company